Secure Authentication and Reliable Cloud Storage Scheme for IoT-Edge-Cloud Integration

Chaudhary, Ajay; Peddoju, Sateesh K.; Chouhan, Vikas

doi:10.1007/s10723-023-09672-z

Cited by 7 publications

(1 citation statement)

References 49 publications

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“…With the rapid development of the Internet and cloud storage technology, as well as the growing popularity of multimedia collection devices, massive audio and other multimedia data has become the main medium for people to obtain and disseminate information, and are being penetrated into human life and work in an all-round way. The emergence of cloud storage technology has reduced users' storage and management costs and brought great convenience to people [1]. However, although audio data stored in the cloud saves users local space and facilitates data sharing between different clients, it also brings problems [2] such as search difficulties, privacy breaches, data insecurity, and lack of verification of retrieval results.…”

Section: Introductionmentioning

confidence: 99%

Multi-User and multi-keyword verifiable encrypted speech retrieval method based on blockchain

Li,

Zhang,

Huang

et al. 2023

Preprint

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Aiming at the existing encrypted speech retrieval schemes that do not support multi-user multi-keyword retrieval, low retrieval efficiency and accuracy, lack of verifiability of encrypted speech retrieval results, and user fairness, a multi-user and multi-keyword verifiable encrypted speech retrieval method based on blockchain was proposed. Firstly, use the advanced encryption standard-128 (AES-128) to encrypt the speech and upload it to the cloud server. Secondly, the Mel-frequency cepstral coefficient (MFCC) and Filter bank (Fbank) speech features are extracted and fused into new MFCC-Fbank features, which are input into the designed CNN-BiGRU model for training. These features are used to extract more robust deep features to construct hash codes and are used as searchable encrypted keywords. Finally, use smart contracts to store encrypted speech hash codes and corresponding index values and manage multi-user keys through trusted institutions. When retrieval, smart contracts are used as trusted third parties for retrieval work, and the designed adaptive homomorphic Message Authentication Code (MAC) algorithm is used to verify the correctness of the retrieval results, ensuring fairness in verification and data privacy. The experimental results show that the proposed method effectively prevents user privacy leakage and improves encrypted speech retrieval accuracy and data security under multi-user and multi-keyword conditions.

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Section: Introductionmentioning

confidence: 99%